As enterprises move from AI experimentation to scaled deployment, data security is undergoing a fundamental shift. With regulations such as the Digital Personal Data Protection (DPDP) Act and the rapid rise of generative AI, organisations are being forced to rethink how data is governed, accessed, and protected across increasingly distributed environments.
In a conversation with Express Computer, Vishal Gauri, CEO, Seclore, and his leadership team, highlight how this transition is reshaping enterprise priorities, why traditional approaches are falling short, and how platforms like ARMOR are enabling organisations to move from risk to readiness.
A perfect storm: AI, data explosion, and compliance
At the heart of this shift lies an unprecedented surge in data creation and consumption. Gauri explains, “The adoption of AI is known as the volume of data that is being created is exploding, the volume of data that is able to be consumed is also exploding.”
He affirms that earlier, much of enterprise data remained untouched due to human limitations. That has now changed dramatically. “As there are millions of files sitting in a file server or in a cloud repository, you would only be able to access very few of them in a human way; that’s changed dramatically.”
At the same time, regulatory pressures are intensifying globally. “Compliance regulations are increasing; if you look at the Middle East markets and North American markets, compliance regulations are changing very quickly,” Gauri points out.
This convergence of AI adoption, data explosion, and regulatory scrutiny creates what he describes as a “perfect storm”, making traditional security approaches inadequate. “Without really having intelligence, traditional data security products will fail, also traditional network security products will fail,” he asserts.
From traditional security to data security intelligence
To address this complexity, Seclore is repositioning itself around what it calls data security intelligence. Gauri explains, “Being intelligent for us means the semantic triad, which is content, context and intent.”
This approach enables organisations to understand not just where data resides but also how it is being used and why, allowing for more precise and adaptive controls. From a product standpoint, the goal is to provide end-to-end visibility and control across environments.
With the ARMOR platform, Seclore provides end-to-end security – complete control right from the visibility to the control. Crucially, this includes both on-premise and cloud environments.
“We wanted to make sure that we support them with on-premise repositories as well as the cloud repositories and create a unified catalogue of the data,” says Gauri. The platform is also designed to be AI-native, built specifically for emerging challenges.
AI: Amplifying both opportunity and risk
While AI unlocks efficiency and scale, it also introduces new categories of risk, often invisible until it is too late.
A key challenge lies in how AI accesses data at scale. “Earlier, if I had access to, let’s say, 100,000 documents, I would open maybe 10 documents in a day… Now with AI, I might do one search and the AI might go and read a thousand documents,” explains Gauri. This shift turns previously dormant data into active risk.
This transforms latent risks into immediate threats. Another emerging concern is data sovereignty.
“Everything you use in ChatGPT or Gemini is always going to the US; it’s not staying here,” he adds. As a result, organisations are increasingly questioning where their data resides and how it is processed.
Security must enable, not restrict
One of the most significant mindset shifts is the role of security itself. Gauri emphasises that security can no longer act as a gatekeeper. “We don’t want to be the people who restrict all the time; we want to be enabling safe usage.”
Blocking AI is not a viable strategy in a competitive environment. Instead, organisations must shift from risk avoidance to risk management. “You have to be willing to turn AI risk into AI readiness,” avers Gauri.
At the core of this transition is context. “The most important concept is context; if you get context right, then you can really allow companies to manage the risk.”
Compliance moves to the boardroom
As risks increase, compliance is no longer just a technical concern—it has become a boardroom priority. For large companies, and especially those in regulated industries, the cost of non-compliance far exceeds the investment in security. “The cost of making sure that governance is in place is nothing compared to the cost of not being compliant.”
This shift is particularly relevant for organisations dealing with sensitive data across geographies.
Rethinking architecture: From perimeter to data-centric security
As hybrid cloud and AI-driven workflows become the norm, traditional perimeter-based security models are no longer sufficient. Instead, organisations must adopt data-centric security models focused on visibility and control.
The guiding principle is clear: “Don’t restrict.”
Rather than slowing innovation, security must evolve to support it safely.
“Look for tools and processes which are going to allow usage of these new technologies and at the same time create guardrails,” adds Gauri.
What will differentiate AI-ready enterprises
Looking ahead, leaders believe that the ability to scale AI will depend on foundational readiness.
Gauri says, “Investment in underlying foundations that will enable AI.” This includes preparing systems, people, and data for AI-driven environments.
Another key factor is organisational confidence in data usage. Enterprises need to be comfortable with what’s happening to their data, otherwise they are underwriting risk.
Equally important is integrating security into the core business fabric. “Think about security not as a separate function… it’s part of whatever the business needs to do,” notes Gauri.
The road ahead
For Seclore, the launch of Armour marks the beginning of a broader transformation. The company plans to build on this foundation by expanding capabilities and use cases.
Alongside product innovation, geographic expansion is also a priority.
Risk to readiness
The rise of AI is forcing enterprises to fundamentally rethink data security. What was once a defensive function is now becoming a strategic enabler of digital transformation. As Vishal Gauri and his team highlight, the future lies in intelligent, context-aware security that allows organisations to use AI confidently while maintaining control over their data.
In this new paradigm, success will not be defined by how well organisations restrict technology, but by how effectively they enable it, securely, responsibly, and at scale.